import os
import torch
import numpy as np
import warnings
def gen_golden_data_simple():
    input_shape = [2048]
    output_shape = [2048]

    warnings.filterwarnings('ignore', category=RuntimeWarning)
    x = np.random.uniform(-100, 100, input_shape).astype(np.float32)
    y = np.random.uniform(0, 4, input_shape).astype(np.float32)

    #print(x)
    #print(y)

    golden = (x**y).astype(np.float32)
    
    os.system("mkdir -p input")
    os.system("mkdir -p output")

    x.tofile("./input/input_x.bin")
    y.tofile("./input/input_y.bin")
    golden.tofile("./output/golden.bin")

if __name__ == "__main__":
    gen_golden_data_simple()

